Summary statistics are numerical values that provide a concise overview of a dataset, helping to describe its main features. They typically include measures of central tendency, such as the mean and median, which indicate the average and middle values of the data, respectively. Additionally, summary statistics often encompass measures of variability, such as the standard deviation and range, which reflect how spread out the data points are.

In the context of data analysis, summary statistics serve as a foundational tool during exploratory data analysis (EDA). They allow analysts to quickly assess the distribution of variables, identify potential anomalies, and extract insights from the data. For instance, a summary table can reveal the statistical distribution of variables, highlighting key points of interest and any unusual patterns that may warrant further investigation ²³.

However, it is essential to recognize that summary statistics alone can be misleading. They may not capture the underlying complexities of the data, as illustrated by the Datasaurus dataset, which demonstrates that different datasets can have identical summary statistics while exhibiting vastly different distributions ¹.